Salidroside is a functionally versatile natural compound from the perennial flowering plant Rhodiola rosea L. Here, we examined obese mice treated with salidroside at the dosage of 50 mg/kg/day for 48 days. Mice treated with salidroside showed slightly decreased food intake, body weight and hepatic triglyceride content. Importantly, salidroside treatment significantly improved glucose and insulin tolerance. It also increased insulin singling in both liver and epididymal white adipose tissue (eWAT). In addition, salidroside markedly ameliorated hyperglycemia in treated mice, which is likely due to the suppression of gluconeogenesis by salidroside as the protein levels of a gluconeogenic enzyme G6Pase and a co-activator PGC-1α were all markedly decreased. Further analysis revealed that adipogenesis in eWAT was significantly decreased in salidroside treated mice. The infiltration of macrophages in eWAT and the productions of pro-inflammatory cytokines were also markedly suppressed by salidroside. Furthermore, the leptin signal transduction in hypothalamus was improved by salidroside. Taken together, these euglycemic effects of salidroside may due to repression of adipogenesis and inflammation in eWAT and stimulation of leptin signal transduction in hypothalamus. Thus, salidroside might be used as an effective anti-diabetic agent.

Background Metabolic abnormalities have recently been widely studied in various cancer types. This study aims to explore the expression profiles of metabolism-related genes (MRGs) in endometrial cancer (EC). Methods We analyzed the expression of MRGs using The Cancer Genome Atlas (TCGA) data to screen differentially expressed MRGs (DE-MRGs) significantly correlated with EC patient prognosis. Functional pathway enrichment analysis of the DE-MRGs was performed. LASSO and Cox regression analyses were performed to select MRGs closely related to EC patient outcomes. A prognostic signature was developed, and the efficacy was validated in part of and the entire TCGA EC cohort. Moreover, we developed a comprehensive nomogram including the risk model and clinical features to predict EC patients’ survival probability. Results Forty-seven DE-MRGs were significantly correlated with EC patient prognosis. Functional enrichment analysis showed that these MRGs were highly enriched in amino acid, glycolysis, and glycerophospholipid metabolism. Nine MRGs were found to be closely related to EC patient outcomes: CYP4F3, CEL, GPAT3, LYPLA2, HNMT, PHGDH, CKM, UCK2 and ACACB. Based on these nine DE-MRGs, we developed a prognostic signature, and its efficacy in part of and the entire TCGA EC cohort was validated. The nine-MRG signature was independent of other clinical features, and could effectively distinguish high- and low-risk EC patients and predict patient OS. The nomogram showed excellent consistency between the predictions and actual survival observations. Conclusions The MRG prognostic model and the comprehensive nomogram could guide precise outcome prediction and rational therapy selection in clinical practice.

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